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Bing He

Publications and source records attributed to Bing He.

At least 73 records · Page 4Linked to original sources
arXiv2022

Active control of particle position by boundary slip in inertial microfluidics

Inertial microfluidic is able to focus and separate particles in microchannels based on the characteristic geometry and intrinsic hydrodynamic effect. Yet, the vertical position of suspended particles in the microchannel cannot be manipulated in real time. In this study, we utilize the boundary slip effect to regulate the parabolic velocity distribution of fluid in the microchannel and present a scheme to active control the vertical position of particles in inertial microfluidics. The flow field of a microchannel with a unilateral slip boundary is equivalent to that of the microchannel widened by the relevant slip length, and the particle equilibrium positions in the two microchannels are consistent consequently. Then, we simulate the lateral migrations of three kinds of typical particles, namely circle, ellipse, and rectangle in the microchannel. Unlike the smooth trajectories of circular particles, the motions of the elliptical and rectangular particles are accompanied by regular fluctuations and non-uniform rotations due to their non-circular geometries. The results demonstrate that the unilateral slip boundary can effectively control the vertical equilibrium position of particles. Thus, the present scheme enables to active manipulate the particles positions in vertical direction and can promote more accurate focusing, separating, and transport in inertial microfluidics.

physics.flu-dyn↗
arXiv2021

Racism is a Virus: Anti-Asian Hate and Counterspeech in Social Media during the COVID-19 Crisis

The spread of COVID-19 has sparked racism and hate on social media targeted towards Asian communities. However, little is known about how racial hate spreads during a pandemic and the role of counterspeech in mitigating this spread. In this work, we study the evolution and spread of anti-Asian hate speech through the lens of Twitter. We create COVID-HATE, the largest dataset of anti-Asian hate and counterspeech spanning 14 months, containing over 206 million tweets, and a social network with over 127 million nodes. By creating a novel hand-labeled dataset of 3,355 tweets, we train a text classifier to identify hate and counterspeech tweets that achieves an average macro-F1 score of 0.832. Using this dataset, we conduct longitudinal analysis of tweets and users. Analysis of the social network reveals that hateful and counterspeech users interact and engage extensively with one another, instead of living in isolated polarized communities. We find that nodes were highly likely to become hateful after being exposed to hateful content. Notably, counterspeech messages may discourage users from turning hateful, potentially suggesting a solution to curb hate on web and social media platforms. Data and code is at http://claws.cc.gatech.edu/covid.

cs.SI↗
arXiv2021

Realization of broadband truly rainbow trapping in gradient-index heterostructures

Unidirectionally propagating waves (UPW) such as topologically protected edge modes and surface magnetoplasmons (SMPs) has been a research hotspot in the last decades. In the study of UPW, metals are usually treated as perfect electric conductors (PECs) which, in general, are the boundary conditions. However, it was reported that the transverse resonance condition induced by the PEC wall(s) may significantly narrow up the complete one-way propagation (COWP) band. In this paper, we propose two ways to achieve ultra-broadband one-way waveguide in terahertz regime. The first way is utilizing the epsilon negative (ENG) metamaterial (MM) and the other one is replacing the PEC boundary with perfect magnetic conductor (PMC) boundary. In both conditions, the total bandwidth of the COWP bands can be efficiently broadened by more than three times. Moreover, based on the ultra-broadband one-way configurations, gradient-index metamaterial-based one-way waveguides are proposed to achieve broadband truly rainbow trapping (TRT). By utilizing the finite element method, the realization of the broadband TRT without backward reflection is verified in gradient-index structures. Besides, giant electric field enhancement is observed in a PMC-based one-way structure with an ultra-subwavelength ($\approx 10^{-4} λ_0$, $λ_0$ is the wavelength in vaccum) terminal, and the amplitude of the electric field is enormously enhanced by five orders of magnitude. Our findings are beneficial for researches on broadband terahertz communication, energy harvesting and strong-field devices.

physics.optics↗
arXiv2021

PETGEN: Personalized Text Generation Attack on Deep Sequence Embedding-based Classification Models

What should a malicious user write next to fool a detection model? Identifying malicious users is critical to ensure the safety and integrity of internet platforms. Several deep learning-based detection models have been created. However, malicious users can evade deep detection models by manipulating their behavior, rendering these models of little use. The vulnerability of such deep detection models against adversarial attacks is unknown. Here we create a novel adversarial attack model against deep user sequence embedding based classification models, which use the sequence of user posts to generate user embeddings and detect malicious users. In the attack, the adversary generates a new post to fool the classifier. We propose a novel end-to-end Personalized Text Generation Attack model, called PETGEN, that simultaneously reduces the efficacy of the detection model and generates posts that have several key desirable properties. Specifically, PETGEN generates posts that are personalized to the user's writing style, have knowledge about a given target context, are aware of the user's historical posts on the target context, and encapsulate the user's recent topical interests. We conduct extensive experiments on two real-world datasets (Yelp and Wikipedia, both with ground-truth of malicious users) to show that PETGEN significantly reduces the performance of popular deep user sequence embedding-based classification models. PETGEN outperforms five attack baselines in terms of text quality and attack efficacy in both white-box and black-box classifier settings. Overall, this work paves the path towards the next generation of adversary-aware sequence classification models.

cs.LG↗
arXiv2021

Blood-derived lncRNAs as potential biomarkers for early cancer diagnosis: The Good, the Bad and the Beauty

Cancer ranks as one of the deadliest diseases worldwide. The high mortality rate associated with cancer is partially due to the lack of reliable early detection methods and/or inaccurate diagnostic tools such as certain protein biomarkers. Cell-free nucleic acids (cfNA) such as circulating long non-coding RNAs (lncRNAs) have recently been proposed as a new class of potential biomarkers that could improve cancer diagnosis. The reported correlation between circulating lncRNA levels and the presence of tumors has triggered a great amount of interest among clinicians and scientists who have been actively investigating their potentials as reliable cancer biomarkers. In this report, we review the progress achieved (the Good) and challenges encountered (the Bad) in the development of circulating lncRNAs as potential biomarkers for early cancer diagnosis. We report and discuss the specificity and sensitivity issues of blood-based lncRNAs currently considered as promising biomarkers for various cancers such as hepatocellular carcinoma, colorectal cancer, gastric cancer and prostate cancer. We also emphasize the potential clinical applications (the Beauty) of circulating lncRNAs both as therapeutic targets and agents, on top of diagnostic and prognostic capabilities. Based on different published works, we finally provide recommendations for investigators who seek to investigate and compare the levels of circulating lncRNAs in the blood of cancer patients compared to healthy subjects by RT-qPCR or Next Generation Sequencing.

q-bio.BM↗
arXiv2021

Numerical simulation of pulmonary airway reopening by the EOS-based multiphase lattice Boltzmann method

The aerosol formation is associated with the rupture of the liquid plug during the pulmonary airway reopening. The fluid dynamics of this process is difficult to predict because the rupture involved complex liquid-gas transition. Equation of state (EOS) plays a key role in the thermodynamic process of liquid-gas transition. Here, we propose an EOS-based multiphase lattice Boltzmann model, in which the nonideal force is directly evaluated by EOSs. This multiphase model is used to model the pulmonary airway reopening and study aerosol formation during exhalation. The numerical model is first validated with the simulations of Fujioka et al.(2008). and the result is in reasonable agreement with their study. Furthermore, two rupture cases with and without aerosol formation are contrasted and analyzed. It is found that the injury on the epithelium in the case with aerosol formation is essentially the same that of without aerosol formation even while the pressure drop in airway increases by about 67%. Then extensive simulations are performed to investigate the effects of pressure drop, thickness of liquid plug and film on aerosol size and the mechanical stresses. The results show that aerosol size and the mechanical stresses increase as the pressure drop enlarges and thickness of liquid plug become thicken, while aerosol size and the mechanical stresses decrease as thickness of liquid film is thicken. The present multiphase model can be extended to study the generation and transmission of bioaerosols which can carry the bioparticles of influenza or coronavirus.

physics.flu-dyn↗
arXiv2021

Lateral Drop Rebound on Hydrophobic and Chemically Heterogeneous Surface

A drop rebounding from a hydrophobic and chemically heterogeneous surface is investigated using the multiphase lattice Boltzmann method. The behaviors of drop rebounding are dependent on the degrees of the hydrophobicity and heterogeneity of the surface. When the surface is homogeneous, the drop rebounds vertically and the height is getting higher and higher with increases of the surface hydrophobicity. When the surface consists of two different hydrophobic surfaces, the drop rebounds laterally towards the low hydrophobic side. The asymmetrical rebounding is because the unbalanced Young's force exerted on the contact line by the high hydrophobic side is greater than that by the low hydrophobic surface. A set of contours of momentum distribution illustrate the dynamic process of drop spreading, shrinking and rebounding. This work promotes the understanding of the rebound mechanism of a drop impacting the surface and also provides a guiding strategy for precisely controlling the lateral behavior of rebounding drops by hydrophobic degrees and heterogeneous surfaces.

physics.comp-ph↗
arXiv2020

Some truncated identities of Gauss

Motivated by the works of Andrews-Merca and Guo-Zeng, we establish some truncated identities of Gauss by using some summation formulas from the works of Zhi-Guo Liu. These give three new expansions for partial sums of Gauss' triangular series.

math.NT↗
arXiv2020

Proofs for two Lambert series identities of Gosper

Applying the theory of modular forms and Lambert series manipulations we establish an Eisenstein series identity. From this formula we confirm a Lambert series identity conjectured by Gosper. Another Lambert series identity of Gosper is also confirmed by using Lambert series manipulations.

math.NT↗
arXiv2020

Proofs for certain Pi_{q}-conjectures of Gosper

In 2001 W. Gosper introduced a constant Pi_{q} and conjectured without proofs many intriguing identities on this constant. In this paper we establish some modular equations of degrees 3 and 5. From these modular equations we confirm two groups of Pi_{q}-identities in Gosper's list. One group involves Pi_{q},Pi_{q^{2}},Pi_{q^{3}} or Pi_{q^{6}} while the other is related to Pi_{q},Pi_{q^{2}},Pi_{q^{5}} or Pi_{q^{10}}.

math.CA↗
arXiv2020

The Role of the Crowd in Countering Misinformation: A Case Study of the COVID-19 Infodemic

Fact checking by professionals is viewed as a vital defense in the fight against misinformation.While fact checking is important and its impact has been significant, fact checks could have limited visibility and may not reach the intended audience, such as those deeply embedded in polarized communities. Concerned citizens (i.e., the crowd), who are users of the platforms where misinformation appears, can play a crucial role in disseminating fact-checking information and in countering the spread of misinformation. To explore if this is the case, we conduct a data-driven study of misinformation on the Twitter platform, focusing on tweets related to the COVID-19 pandemic, analyzing the spread of misinformation, professional fact checks, and the crowd response to popular misleading claims about COVID-19. In this work, we curate a dataset of false claims and statements that seek to challenge or refute them. We train a classifier to create a novel dataset of 155,468 COVID-19-related tweets, containing 33,237 false claims and 33,413 refuting arguments.Our findings show that professional fact-checking tweets have limited volume and reach. In contrast, we observe that the surge in misinformation tweets results in a quick response and a corresponding increase in tweets that refute such misinformation. More importantly, we find contrasting differences in the way the crowd refutes tweets, some tweets appear to be opinions, while others contain concrete evidence, such as a link to a reputed source. Our work provides insights into how misinformation is organically countered in social platforms by some of their users and the role they play in amplifying professional fact checks.These insights could lead to development of tools and mechanisms that can empower concerned citizens in combating misinformation. The code and data can be found in http://claws.cc.gatech.edu/covid_counter_misinformation.html.

cs.SI↗
arXiv2020

Prediction of repurposed drugs for treating lung injury in COVID-19

Coronavirus disease (COVID-19) is an infectious disease discovered in 2019 and currently in outbreak across the world. Lung injury with severe respiratory failure is the leading cause of death in COVID-19, brought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there still lacks efficient treatment for COVID-19 induced lung injury and acute respiratory failure. Inhibition of Angiotensin-converting enzyme 2 (ACE2) caused by spike protein of SARS-CoV-2 is the most plausible mechanism of lung injury in COVID-19. We propose two candidate drugs, COL-3 (a chemically modified tetracycline) and CGP-60474 (a cyclin-dependent kinase inhibitor), for treating lung injuries in COVID-19, based on their abilities to reverse the gene expression patterns in HCC515 cells treated with ACE2 inhibitor and in human COVID-19 patient lung tissues. Further bioinformatics analysis shows that twelve significantly enriched pathways (P-value <0.05) overlap between HCC515 cells treated with ACE2 inhibitor and human COVID-19 patient lung tissues, including signaling pathways known to be associated with lung injury such as TNF signaling, MAPK signaling and Chemokine signaling pathways. All these twelve pathways are targeted in COL-3 treated HCC515 cells, in which genes such as RHOA, RAC2, FAS, CDC42 have reduced expression. CGP-60474 shares eleven of twelve pathways with COL-3 with common target genes such as RHOA. It also uniquely targets genes related to lung injury, such as CALR and MMP14. In summary, this study shows that ACE2 inhibition is likely part of the mechanisms leading to lung injury in COVID-19, and that compounds such as COL-3 and CGP-60474 have the potential as repurposed drugs for its treatment.

q-bio.TO↗
arXiv2020

Hecke-type identities associated with definite quadratic forms

Since the study by Jacobi and Hecke, Hecke-type series have received a lot of attention. Unlike such series associated with indefinite quadratic forms, identities on Hecke-type series associated with definite quadratic forms are quite rare in the literature. Motivated by the works of Liu, we first establish many parameterized identities with two parameters by employing different $q$-transformation formulas and then deduce various Hecke-type identities associated with definite quadratic forms by specializing the choice of these two parameters. As applications, we utilize some of these Hecke-type identities to establish families of inequalities for several partition functions. Our proofs heavily rely on some formulas from the work of Zhi-Guo Liu.

math.NT↗
arXiv2020

Hecke-type series involving infinite products

Since the study by Jacobi and Hecke, Hecke-type series have received extensive attention. Especially, Hecke-type series involving infinite products have attracted broad interest among many mathematicians including Kac, Peterson, Andrews, Bressoud and Liu. Motivated by the works of these people, we study Hecke-type series involving infinite products. In particular, we establish some Hecke-type series involving infinite products and then obtain the truncated versions of these series as well as some other known series of the same type. As consequences, three families of inequalities for certain partition functions are also presented. Our proofs heavily rely on a formula from the work of Zhi-Guo Liu.

math.NT↗
arXiv2019

Synchronous oscillations locked on classical energy levels by two cooperating drives

It is intuitively imagined that the energy of a classical object always takes continues values and can hardly be confined to discrete ones like the energy levels of microscopic systems. Here, we demonstrate that such classical energy levels against intuition can be created through a previously unknown synchronization process for nonlinearly coupled macroscopic oscillators driven by two equally strong fields. Given the properly matched frequencies of the two drive fields, the amplitude and phase of an oscillator will be frozen on one of a series of determined trajectories like energy levels, and the phenomenon exists for whatever drive intensity beyond a threshold. Interestingly, the oscillator's motion can be highly sensitive to its initial condition but, unlike the aperiodicity in chaotic motion, it will nonetheless end up on such fixed energy levels. Upon reaching the stability, however, the oscillations on the energy levels are robust against noisy perturbation.

nlin.PS↗
arXiv2019

Transmission Nonreciprocity in a Mutually Coupled Circulating Structure

Breaking Lorentz reciprocity was believed to be a prerequisite for nonreciprocal transmissions of light fields, so the possibility of nonreciprocity by linear optical systems was mostly ignored. We put forward a structure of three mutually coupled microcavities or optical fiber rings to realize optical nonreciprocity. Although its couplings with the fields from two different input ports are constantly equal, such system transmits them nonreciprocally either under the saturation of an optical gain in one of the cavities or with the asymmetric couplings of the circulating fields in different cavities. The structure made up of optical fiber rings can perform nonreciprocal transmissions as a time-independent linear system without breaking Lorentz reciprocity. Optical isolation for inputs simultaneously from two different ports and even approximate optical isolator operations are implementable with the structure.

physics.optics↗
arXiv2019

On certain q-trigonometric identities

Finding theta function (or $q$-)analogues for well-known trigonometric identities is an interesting topic. In this paper, we first introduce the definition of $q$-analogues for $\mathrm{tan}z$ and $\mathrm{cot}z$ and then apply the theory of elliptic functions to establish a theta function identity. From this identity we deduce two $q$-trigonometric identities involving $\mathrm{tan}_{q}z$ and $\cot_{q}z,$ which are theta function analogues for two well-known trigonometric identities concerning $\mathrm{tan}z$ and $\cot z.$ Some other $q$-trigonometric identities are also given.

math.GM↗